Technological development has led to a boom in the communication device market. In wireless communication systems, communication devices such as mobile phones, wireless Personal Digital Assistants (PDAs), Wi-Fi-enabled laptops, Bluetooth headsets, Radio Frequency Identifier (RFID) tags, wireless medical devices, ZigBee sensors, Internet of Things (IoT) devices, and the like, are being used extensively for a multitude of applications. These communication devices include components such as RF Integrated Circuits (RFICs) used in Modulator-Demodulators (MODEMS), Bluetooth, Wi-Fi, and Global Positioning System (GPS) circuits for communication and processing of signals in the RF spectrum.
Extended aging test results reveal that electrical characteristics of components such as RFICs drift from their designed values due to various external factors such as stress, temperature and so on. Similarly, various internal factors such as transient currents, electromigration, device aging, and the like, also contribute to drifting of electrical characteristics. Drifting of electrical characteristics may result in reduced RF functionality and eventually may contribute to device performance degradation. To handle minor drifts in electrical characteristics, the communication devices are provided with factory estimated calibration data (error compensation data) during an initial factory calibration process. However, this error compensation data may no longer be accurate when the drifting of electrical characteristics of RF components of the communication devices increases due to various factors such as aging effects.
Thus, recalibration of the communication devices may be desired so as to maintain device performance. Currently, such recalibration can be performed with assistance from factory signal generators available at the factory or at service centers. Here, the communication device (also referred to as a Device Under Test (DUT)) is directly connected with a factory signal generator (i.e., Agilient, CM W500) to retune the communication device and bring it back to a calibrated state. Thus, with current methods of recalibration the communication devices are transported to the factory or service centers. In addition, the communication devices are connected with external equipment to diagnose whether they require recalibration. Further, such diagnostics are performed at set times and seamless monitoring is currently unavailable.
Furthermore, in scenarios where the communication devices to be recalibrated are deployed on site at remote locations, the current recalibration methods described above are not practical. By bringing the communication devices to the factory from the deployment sites, they no longer fulfill the purpose for which they were deployed at the remote locations. Communication devices such as IoT devices are expected to operate flawlessly on site for relatively long periods (i.e., up to a decade or longer). Alternatively, the IoT devices may be recalibrated on site. However, carrying a factory signal generator to the deployed locations may not be a practical option either given that the communication devices may be deployed in locations and conditions that are difficult to reach. Thus, maintaining the communication devices in a calibrated state to ensure device performance remains a challenge in many practical situations.